ATTRIBUTE REDUCTION ALGORITHM BASED ON COGNITIVE MODEL OF GRANULAR COMPUTING IN INCONSISTENT DECISION INFORMATION SYSTEMS

被引：1
|
作者：
Tang, Xiao [1 ]
Shu, Lan [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
来源：
TEHNICKI VJESNIK-TECHNICAL GAZETTE | 2014年 / 21卷 / 01期
关键词：
attribute reduction; cognitive model; granular computing; inconsistent decision table; ROUGH SET-THEORY; KNOWLEDGE REDUCTION;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This article aims to explore a new method of attribute reduction in inconsistent decision information systems. By analyzing the connection of attribute reduction theory and cognitive science, an attribute reduction algorithm based on cognitive model of granular computing is proposed in this paper. Algorithm analysis and numerical experiment show the validity of the proposed attribute reductions algorithm. The method can be applied to both consistent and inconsistent information systems. The proposed model also provides a new model and thinking to study the connection of human's cognition and notion. It is useful to the development of cognitive model.
引用
收藏
页码：49 / 54
页数：6
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